The disclosed embodiments relate generally to red-eye repair techniques, and more particularly, to specific characterization, discernment, and repair techniques utilizing multiple recognition channels (e.g., red, golden, and white recognition channels). In certain embodiments, the red-eye repair techniques may be applied to an image automatically with limited or no input from a user.
In photography, red-eye is the occurrence of glowing red pupils in a color photograph due to eye shine. Red-eye is believed to be caused by the red reflection of the blood vessels in the retina when a strong and sudden light strikes the eye. The tonality and intensity of red-eye may vary from person to person based on ethnicity, pigmentation levels, and other factors. Today's compact digital cameras commonly used in embedded systems exacerbate the problem of red-eye artifacts because of the proximity of the camera's flash unit and the lens. One common technique to mitigate red-eye is to use multiple flashes to contract the pupils before capturing the final image. However, this provides incomplete red-eye reduction, lengthens the amount of time needed to capture the final image, and presents more of a drain on the camera device's power source.
Other techniques that attempt to programmatically mitigate red-eye only work well when red-eye artifacts are actually predominantly red in color and/or are present in familiar orientations and shapes, i.e., front-facing and circular. Still other existing red-eye repair techniques use red-eye replacement techniques that are overly simplified, often resulting in jagged pupils or solid black pupils that may actually make the photo look more unnatural and less realistic than the original, unaltered photo with red-eye artifacts.
In addition to red artifacts, the inventor has noticed that the color of a “red-eye” may also be golden (i.e., a mixture of various degrees of red, orange, yellow, and white), or even pure white. This condition can occur, e.g., when photographing faces using a strong light source such as a flash that exists at a small displacement from the lens, and most often when the pupil is wide open. While the return signal from a red-eye artifact has a predominantly red hue, the hue can be altered by the color filter array chromaticities in the camera image sensor, and the color may also be distorted by erroneous clipping of the image's red, green, and blue signals during color processing. This artifact can be exacerbated by the gain factors required in low-light situations in which the flash is required. Further, artifacts may come in a variety of shapes, sizes, and overlapping topological layers. Specular shine, i.e., the reflection of light off the cornea or sclera (i.e., the whites of the eyes), is another aspect that may be considered in red-eye repair and replacement to achieve photographically reasonable results.
Accordingly, there is a need for techniques to implement a programmatic solution to red-eye repair that is robust enough to handle a large number of red-eye cases and color types automatically. By discerning between red, golden, and white eye artifacts, and locating and characterizing human faces in an image, for example, more specific automatic repair techniques may be employed to achieve photographically reasonable results.